Abstract
Globally, over 500 universities now offer data science courses at undergraduate or postgraduate level and, in research-intensive universities, these courses are typically underpinned by academic research in statistics, machine learning and computer science departments and, increasingly, in multidisciplinary data science institutes. Much has been written about the academic challenges of data science from the perspective of its core academic disciplines and from its application domains, ranging from sciences and engineering through to arts and humanities. However, relatively little has been written about the institutional information technology (IT) support challenges entailed by this rapid growth in data science. This paper sets out some of these IT challenges and examines competing support strategies, service design and financial models through the lens of academic IT support services.
Original language | English |
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Title of host publication | EUNIS 2016 Proceedings |
Subtitle of host publication | European University Information Systems 22nd Annual Congress |
Editors | Yiannis Salmatzidis |
Place of Publication | Thessaloniki |
Publisher | Aristotle University of Thessaloniki, Greece |
Pages | 283-285 |
ISBN (Electronic) | ISSN 2409-1340 |
Publication status | Published - 11 Jun 2016 |
Event | EUNIS 2016 - Aristotle University of Thessaloniki, Thessaloniki, Greece Duration: 8 Jun 2016 → 10 Jun 2016 |
Conference
Conference | EUNIS 2016 |
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Country/Territory | Greece |
City | Thessaloniki |
Period | 8/06/16 → 10/06/16 |
Keywords
- Data Science
- management strategies